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1.
Rev. cuba. invest. bioméd ; 40(1): e670, ene.-mar. 2021. tab, graf
Article in Spanish | LILACS, CUMED | ID: biblio-1289442

ABSTRACT

Introducción: Las motivaciones para elegir las carreras universitarias determinan en buena medida el desempeño profesional, de allí la necesidad de contar con instrumentos válidos y confiables para su estudio. Objetivo: Validar una escala para evaluar las motivaciones para estudiar Estomatología en alumnos cubanos. Métodos: Estudio de tipo instrumental, transversal y multicéntrico, que incluyó estudiantes de nueve universidades cubanas. A partir de un instrumento en español validado en estudiantes latinoamericanos de medicina, se realizó un análisis factorial exploratorio por mínimos cuadrados no ponderados. Luego se realizó un análisis factorial confirmatorio y se midió la consistencia interna con el alpha de Cronbach. Resultados: Se incluyó a 1324 participantes, de los cuales el 66,8 por ciento fueron mujeres y la media de la edad fue 21,2 ± 1,8 años. Sobre la base de una matriz de correlaciones, la prueba de Bartlett arrojó indicadores significativos (p < 0,05) y el índice KMO fue superior a 0,8. La varianza explicada fue superior al 50 por ciento y el análisis paralelo sugirió solo 2 factores. De la escala inicial, el análisis factorial sugirió eliminar los ítems 4 y 5 (factor 1), 9 y 12 (factor 2) y el ítem 1, por lo que el modelo quedó conformado por 7 ítems, 3 para el factor 1 y 4 para el factor 2. El ajuste e índices fueron adecuados, lo que demostró validez de constructo. Conclusión: La escala de motivaciones para estudiar Estomatología demostró ser válida y confiable, y está conformada por dos dominios que denotan aspectos sociales y económicos(AU)


Introduction: The motivations for the choice of university studies determine professional performance to a considerable extent. Hence the need for valid, reliable tools to evaluate them. Objective: Validate a scale to evaluate motivational reasons to study dentistry among Cuban students. Methods: An instrumental cross-sectional multicenter study was conducted which included students from nine Cuban universities. Based on a tool in Spanish validated in Latin American medical students, exploratory factor analysis was performed by unweighted least squares. Confirmatory factor analysis was then carried out, and internal consistency was measured with Cronbach's alpha. Results: A total 1 324 participants were included, of whom 66.8 percent were women; mean age was 21.2 ± 1.8 years. Based on a correlation matrix, Bartlett's test yielded significant indicators (p < 0.05), and the KMO index was above 0.8. Explained variance was above 50 percent, and parallel analysis suggested only two factors. Factor analysis suggested to remove the following items from the initial scale: 4 and 5 (factor 1), 9 and 12 (factor 2) and 1, as a result of which the model would consist of 7 items: 3 for factor 1 and 4 for factor 2. The adjustment and the indices were appropriate, which showed construct validity. Conclusion: The scale for motivations to study dentistry was found to be valid and reliable. It consists of two domains denoting social and economic aspects(AU)


Subject(s)
Humans , Male , Female , Students, Medical , Universities , Least-Squares Analysis , Demography , Oral Medicine , Dentistry , Motivation , Cross-Sectional Studies , Multicenter Study
2.
Article in Chinese | WPRIM | ID: wpr-888010

ABSTRACT

This study explores the emulsifying material basis of Angelicae Sinensis Radix volatile oil (ASRVO) based on partial least squares (PLS) method and hydrophile-lipophile balance (HLB) value.The turbidity of ASRVO emulsion samples from Gansu,Yunnan,and Qinghai was determined and the chemical components in the emulsion were analyzed by GC-MS.The PLS model was established with the chemical components as the independent variable and the turbidity as the dependent variable and evaluated with indexes R~2X and R~2Y.The chemical components which were in positive correlation with the turbidity were selected and the HLB values were calculated to determine the emulsification material basis of ASRVO.The PLS models for the 81 emulsion samples had high R~2X and R~2Y values,which showed good fitting ability.Seven chemical components,2-methoxy-4-vinylphenol,trans-ligustilide,3-butylidene-1(3H)-isobenzofuranone,dodecane,1-methyl-4-(1-methylethylidene)-cyclohexene,trans-beta-ocimene,and decane,had positive correlation with turbidity.Particularly,the HLB value of 2-methoxy-4-vinylphenol was 4.4,which was the HLB range of surfactants to be emulsifiers and 2-methoxy-4-vinylphenol was positively correlated with turbidity of the ASRVO emulsion samples from the main producing area.Therefore,2-methoxy-4-vinylphenol was the emulsifying material basis of ASRVO.The selected emulsifying substances can lay a foundation for exploring the emulsification mechanism and demulsification solution of ASRVO.


Subject(s)
China , Emulsions , Least-Squares Analysis , Oils, Volatile , Surface-Active Agents
3.
Article in Chinese | WPRIM | ID: wpr-879162

ABSTRACT

In order to establish a rapid and non-destructive evaluation method for the identification of Armeniacae Semen Amarum and Persicae Semen from different origins, the spectral information of Armeniacae Semen Amarum and Persicae Semen in the range of 898-1 751 nm was collected based on hyperspectral imaging technology. Armeniacae Semen Amarum and Persicae Semen from different origins were collected as research objects, and a total of 720 Armeniacae Semen Amarum samples and 600 Persicae Semen samples were used for authenticity discrimination. The region of interest(ROI) and the average reflection spectrum in the ROI were obtained, followed by comparing five pre-processing methods. Then, partial least squares discriminant analysis(PLS-DA), support vector machine(SVM), and random forest(RF) method were established for classification models, which were evaluated by the confusion matrix of prediction results and receiver operating characteristic curve(ROC). The results showed that in the three sample sets, the se-cond derivative pre-processing method and PLS-DA were the best model combinations. The classification accuracy of the test set under the 5-fold cross-va-lidation was 93.27%, 96.19%, and 100.0%, respectively. It was consistent with the confusion matrix of the predicted results. The area under the ROC curve obtained the highest values of 0.992 3, 0.999 6, and 1.000, respectively. The study revealed that the near-infrared hyperspectral imaging technology could accurately identify the medicinal materials of Armeniacae Semen Amarum and Persicae Semen from different origins and distinguish the authentication of these two varieties.


Subject(s)
Drugs, Chinese Herbal , Hyperspectral Imaging , Least-Squares Analysis , Semen , Support Vector Machine , Technology
4.
Article in Chinese | WPRIM | ID: wpr-879161

ABSTRACT

Three cancer cell lines including gastric cancer SGC-7901, HGC-27, and MGC-803 cells were employed to evaluate the bioactivity of seven Dendrobium species. Simultaneously, these Dendrobium species were assessed with UPLC-Q-TOF-MS, and 504 common peaks were found. Based on the hypothesis that biological effects varied with differences in components, multivariate relevance analysis for chemical component-activity relationship of Dendrobium, including grey relation(GRA) and partial least squares(PLS) analysis were performed to evaluate the contribution of each identified component. The target peaks were identified by standards toge-ther with databases of Dendrobium, Nature Chemistry, MassBank, etc. Finally, four active components, including 3,5,9-trihydroxy-23-methylergosta-7,22-dien-6-one, diacylglycerol(14∶1/22∶6/0∶0), pipercitine, and 22-tricosenoic acid, might have negative effect on the growth of gastric cancer cells.


Subject(s)
Dendrobium , Humans , Least-Squares Analysis , Multivariate Analysis , Stomach Neoplasms/drug therapy
5.
Article in Chinese | WPRIM | ID: wpr-879069

ABSTRACT

Spatial distribution uniformity is the critical quality attribute(CQA) of Ginkgo Leaves Tablets, a variety of big brand traditional Chinese medicine. The evaluation of the spatial distribution uniformity of active pharmaceutical ingredients(APIs) in Ginkgo Leaves Tablets is important in ensuring their stable and controllable quality. In this study, hyperspectral imaging technology was used to construct the spatial distribution map of API concentration based on three prediction models, further to realize the visualization research on the spatial distribution uniformity of Ginkgo Leaves Tablets. The region of interest(ROI) was selected from each Ginkgo Leaves Tablet, with length and width of 50 pixels, and a total of 2 500 pixels. Each pixel had 288 spectral channels, and the number of content prediction data could reach 1×10~5 for a single sample. The results of the three models showed that the Partial Least Squares(PLS) model had the highest prediction accuracy, with calibration set determination coefficient R_(pre)~2 of 0.987, prediction set determination coefficient R_(pre)~2 of 0.942, root mean square error of calibration(RMSEC) of 0.160%, and root mean square error of prediction(RMSEP) of 0.588%. The classical least-squares(CLS) model had a greater prediction error, with the RMSEP of 0.867%. Multivariate Curve Resolution-Alternating Least Square(MCR-ALS) model showed the worst predictive ability among the three models, and it couldn't realize content prediction. Based on the prediction results of PLS and CLS models, the spatial distribution map of APIs concentration was obtained through three-dimensional data reconstruction. Furthermore, histogram method was used to evaluate the spatial distribution uniformity of API. The data showed that the spatial distribution of APIs in Ginkgo Leaves Tablets was relatively uniform. The study explored the feasibility of visualization of spatial distribution of Ginkgo Leaves Tablets based on three models. The results showed that PLS model had the highest prediction accuracy, and MCR-ALS model had the lowest prediction accuracy. The research results could provide a new strategy for the visualization method of quality control of Ginkgo Leaves Tablets.


Subject(s)
Calibration , Ginkgo biloba , Least-Squares Analysis , Medicine, Chinese Traditional , Plant Leaves , Quality Control , Spectroscopy, Near-Infrared , Tablets
6.
Article in Chinese | WPRIM | ID: wpr-879066

ABSTRACT

For the field detection problems of critical quality attribute(CQA) of moisture content in traditional Chinese medicine(TCM) manufacturing process, big brand TCM Tongren Niuhuang Qingxin Pills were used as the carrier, to establish a moisture content NIR field detection model with or without cellophane in real world production with use of near infrared(NIR) spectroscopy combined with stoichiometry. With the moisture content determined by drying method as reference value, the partial least square method(PLS) was used to analyze the correlation between the spectrum and the moisture reference value. Then the spectral pretreatment methods were screened and optimized to further improve the accuracy and stability of the model. The results showed that the best quantitative model was developed by the spectral data pretreatment of standard normal variate(SNV) with the latent variable factor number of 2 and 7 of Tongren Niuhuang Qingxin Pills with or without cellophane samples. The prediction coefficient of determination(R_(pre)~2) and standard deviation of prediction(RMSEP) of the model with cellophane samples were 0.765 7 and 0.157 2%; R_(pre)~2 and RMSEP of the model without cellophane samples were 0.772 2 and 0.207 8%. The NIR quantitative models of moisture content of Tongren Niuhuang Qingxin Pills with and without cellophane both showed good predictive performance to realize the rapid, accurate and non-destructive quantitative analysis of moisture content in such pills, and provide a method for the field quality control of the critical chemical attributes of moisture in the manufacturing of big brand TCM.


Subject(s)
Drugs, Chinese Herbal , Least-Squares Analysis , Medicine, Chinese Traditional , Spectroscopy, Near-Infrared
7.
Article in Chinese | WPRIM | ID: wpr-878918

ABSTRACT

Near-infrared spectroscopy(NIRS) combined with band screening method and modeling algorithm can be used to achieve the rapid and non-destructive detection of the traditional Chinese medicine(TCM) production process. This paper focused on the ginkgo leaf macroporous resin purification process, which is the key technology of Yinshen Tongluo Capsules, in order to achieve the rapid determination of quercetin, kaempferol and isorhamnetin in effluent. The abnormal spectrum was eliminated by Mahalanobis distance algorithm, and the data set was divided by the sample set partitioning method based on joint X-Y distances(SPXY). The key information bands were selected by synergy interval partial least squares(siPLS); based on that, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA) and Monte Carlo uninformative variable(MC-UVE) were used to select wavelengths to obtain less but more critical variable data. With selected key variables as input, the quantitative analysis model was established by genetic algorithm joint extreme learning machine(GA-ELM) algorithm. The performance of the model was compared with that of partial least squares regression(PLSR). The results showed that the combination with siPLS-CARS-GA-ELM could achieve the optimal model performance with the minimum number of variables. The calibration set correlation coefficient R_c and the validation set correlation coefficient R_p of quercetin, kaempferol and isorhamnetin were all above 0.98. The root mean square error of calibration(RMSEC), the root mean square error of prediction(RMSEP) and the relative standard errors of prediction(RSEP) were 0.030 0, 0.029 2 and 8.88%, 0.041 4, 0.034 8 and 8.46%, 0.029 3, 0.027 1 and 10.10%, respectively. Compared with the PLSR me-thod, the performance of the GA-ELM model was greatly improved, which proved that NIRS combined with GA-ELM method has a great potential for rapid determination of effective components of TCM.


Subject(s)
Algorithms , Ginkgo biloba , Least-Squares Analysis , Plant Leaves , Spectroscopy, Near-Infrared
8.
Braz. arch. biol. technol ; 64: e21190760, 2021. tab, graf
Article in English | LILACS | ID: biblio-1249208

ABSTRACT

Abstract The purpose of this research was to discriminate soil fractions using mineralogical and elemental analyses and to show those fractions that present greater contribution to the soil mass attenuation coefficient (μ) as well as their partial cross-sections for photoelectric absorption (PA), coherent scattering (CS) and incoherent scattering (IS). Soil samples from different places of Brazil classified as Yellow Argisol, Yellow Latosol and Gray Argisol were submitted to elemental and mineralogical analyses through energy dispersive X-ray fluorescence (EDXRF) and Rietveld Method with X-ray diffraction data (RM-XRD). The mixture rule was utilized to calculate μ of each soil. The EDXRF analysis showed as predominant elements Si, Al, Fe and Ti oxides. The highest contents were Si (914.3 to 981.3 g kg-1) in the sand fractions, Al (507.9 to 543.7 g kg-1) and Fe (32.5 to 76.7 g kg-1) in the clay fractions, and Ti (18.0 to 59.0 g kg-1) in the silt fractions. The RM-XRD allowed identifying that the sand fractions are predominantly made of quartz (913.3 to 995.0 g kg-1), while the clay greatest portion is made of kaolinite (465.0 to 660.6 g kg-1) and halloysite (169.0 to 385.0 g kg-1). The main effect responsible for μ was IS (50 to 61.4%) followed by PA (28 to 40.1%) and CS (9.9 to 10.6%). By using the principal component analysis (PC-1: 57.5% and PC-2: 20.9%), the samples were differentiated through the discrimination between physical, chemical and mineralogical properties. The results obtained suggest that general information about the radiation interaction in soils can be obtained through the elemental and mineralogical analyses of their fractions.


Subject(s)
Soil Characteristics/analysis , Disaster Prevention and Mitigation , Least-Squares Analysis , Principal Component Analysis
9.
Rev. colomb. psiquiatr ; 49(3): 154-161, jul.-set. 2020. tab
Article in Spanish | LILACS, COLNAL | ID: biblio-1149821

ABSTRACT

RESUMEN Objetivo: Analizar las propiedades psicométricas, estructura interna y relación con indicadores antropométricos del Body Shape Questionnaire (BSQ) en universitarios mexicanos, partiendo de un enfoque de la invarianza de medición. Métodos: Se realizó un estudio instrumental, orientado a la evaluación de las propiedades psicométricas, validez y fiabilidad, del BSQ. Se realizó análisis de invarianza de la medición por el método de estimación mínimos cuadrados ponderados con varianza ajustada y correlaciones policóricas, previa evaluación de diferentes modelos de medición del BSQ en cada grupo. Las puntuaciones de la versión final se correlacionaron con indicadores antropométricos mediante el coeficiente de correlación de Pearson. Resultados: En el análisis dimensional, todos los modelos previos del BSQ presentan índices de ajuste favorables, aunque aquellos de un solo factor presente son los que tienen evidencia más robusta. Se aceptó la invarianza configural, lo que indica que la estructura unidimensional es común a varones y mujeres. Sin embargo, las cargas factoriales de 16 ítems fueron estadísticamente diferentes entre los grupos, por lo que se descartaron y se obtuvo una versión de 18 ítems (BSQ-18), que se considera invariante respecto al sexo. Además, hay relación directa entre las puntuaciones de la versión del BSQ-18 y el índice de masa corporal, la circunferencia de cintura y el porcentaje de grasa. En cuanto a la fiabilidad, se hallaron indicadores satisfactorios. Conclusiones: El BSQ-18 es aplicable tanto a varones como a mujeres y tiene indicadores de fiabilidad elevados que posibilitan su uso en entornos clínicos para la evaluación en el abordaje de trastornos de la conducta alimentaria y obesidad en jóvenes universitarios.


ABSTRACT Objective: To analyse the psychometric properties, internal structure, and relationship with anthropometric indicators of the Body Shape Questionnaire (BSQ) among Mexican university students according to the measurement invariance approach. Methods: An instrumental study was carried out to assess the psychometric properties, validity, and reliability of the BSQ. The analysis of the measurement invariance was performed using the Least Squares Estimation, and weighted by adjusted variance and polychoric correlations after assessing different measurement models for BSQ in each group. The scores of the final version were correlated with anthropometric indicators by the Pearson correlation coefficient. Results: As regards the dimensional analysis, all of the previous models for BSQ have favourable adjustment rates, although those with a single factor show more robust evidence. The configural invariance was accepted; suggesting that the one-dimensional structure is common for both men and women. However, 16-item factorial loadings were statistically different between the groups. Hence, they were discarded and an 18-item version (BSQ-18) was obtained, which is considered invariant as regards gender. In addition, there is a direct relationship between the scores of the BSQ-18 version and the body mass index, waist circumference, and fat percentage. Satisfactory indicators were found as regards stability. Conclusions: The BSQ-18 can be used with men and women, and has high reliability indicators to be conducted in clinical settings to assess eating disorders and obesity among university students


Subject(s)
Humans , Male , Female , Adolescent , Somatotypes , Students , Feeding and Eating Disorders , Body Mass Index , Least-Squares Analysis , Surveys and Questionnaires , Waist Circumference , Gender Identity
11.
Article in Chinese | WPRIM | ID: wpr-827973

ABSTRACT

A rapid analysis method based on ultraviolet-visual(UV-Vis) spectroscopy, near infrared(NIR) spectroscopy and multivariable data analysis was established for quality evaluation of Shengxuebao Mixture. The contents of eight active ingredients of Shengxuebao Mixture including albiflorin, paeoniflorin, 2, 3, 5, 4'-tetra-hydroxy-stilbene-2-O-β-D-glucopyranoside, specnuezhenide,ecliptasaponin D, emodin, calycosin-7-glucoside and astragaloside Ⅳ were simultaneously detected by using this method. HPLC-UV-MS was used as a reference method for determining the contents of these ingredients. Partial least squares(PLS) analysis was implemented as a linear method for multivariate models calibrated between UV spectrum/NIR spectrum and contents of 8 ingredients. Finally, the performance of the model was evaluated by 24 batches of test samples. The results showed that both UV-Vis and NIR models gave a good calibration ability with an R~2 value above 0.9, and the prediction ability was also satisfactory, with an R~2 value higher than 0.83 for UV-Vis model and higher than 0.79 for NIR model. The overall results demonstrate that the established method is accurate, robust and fast, therefore, it can be used for rapid quality evaluation of Shengxuebao Mixture.


Subject(s)
Calibration , Chromatography, High Pressure Liquid , Drugs, Chinese Herbal , Least-Squares Analysis , Mass Spectrometry , Spectroscopy, Near-Infrared
12.
Article in Chinese | WPRIM | ID: wpr-777500

ABSTRACT

The efficacy and quality of Gastrodia elata from different producing areas are significant difference. The identification of producing area is helpful for the scientific and reasonable usage of medicinal material. Application near infrared spectroscopy( NIR) together with variance spectra,principal component analysis( PCA),interval partial least squares( i PLS) and genetic algorithm( GA),the characteristic spectra of G. elata from inside and outside of Yunnan province( except Zhaotong) and Zhaotong were extracted,and the pattern recognition models of i PLS-DA and GA-SVM were built,and the suitability of the models were also validated. The results showed that the prediction accuracy of i PLS-DA model was 96. 15%,the values of R2,RMSECV and RMSEP were 0. 893,0. 224 and0. 321,respectively. The prediction accuracy of GA-SVM model was 100% and RMSECV was 0. 719 4. Both methods could identify G. elata from different producing area preferably. Further,two-dimensional spectroscopy analysis was conducted for the characteristic spectra extracted by i PLS and GA. The results showed that the differential spectra of G. elata from outside and inside Yunnan were mainly located in the absorption areas of the stretch,bending and double frequency of C-H,C-N,O-H and N-H bonds of polysaccharides,aromatic hydrocarbon,amides and starch. The differential spectra of G. elata from outside Yunnan and Zhaotong were mainly located in the absorption areas of the stretch,bending and double frequency of C-H,O-H and N-H bonds of vegetable protein,aromatic hydrocarbon,polysaccharides,and alcohols. The differential spectra of G. elata from inside Yunnan and Zhaotong were mainly located in the absorption areas of the stretch,bending,transformation and double frequency of CHO,N-H,C-H,O-H and HOH bonds of lignin,aromatic hydrocarbon,alcohols,polysaccharides and aliphatics. Effective recognition of different producing areas and exploration the difference of component of G. elata could be conducted through NIR combined with multivariable selection and two-dimensional spectroscopy,which provided the basis for the reasonable development and efficient utilization of G. elata.


Subject(s)
China , Gastrodia , Least-Squares Analysis , Principal Component Analysis , Spectroscopy, Near-Infrared
13.
Article in Chinese | WPRIM | ID: wpr-774517

ABSTRACT

Near infrared spectroscopy(NIRS) was used for rapid quantitative analysis of saponins in Pien Tze Huang troches and powders. The near infrared spectra of Pien Tze Huang were collected,and the contents of notoginsenoside R1,ginsenoside Rg1 and ginsenoside Rb1 in Pien Tze Huang were determined by high performance liquid chromatography(HPLC) as the reference values. Then the near infrared spectra of the samples were associated with the reference values to establish the quantitative analysis models by using partial least squares(PLS) method. Finally,the models were verified by unknown samples. The results showed that root mean square error of cross-validation(RMSECV) of R1,Rg1,Rb1 and the total content was 0.095 1,0.555,0.414,0.960 mg·g-1 for the troches models,0.085 6,0.443,0.405,0.913 mg·g-1 for the powders models. After external validations,root mean square error of prediction(RMSEP) of R1,Rg1,Rb1 and the total content was 0.111,0.274,0.276,0.807 mg·g-1 for the troches models,0. 059 2,0. 322,0. 327,0. 705 mg·g-1 for the powders models. The averages of relative standard deviation between the predicted values and the chemical measured values were all less than 2.0%. According to the results of paired-t tests at the level of α = 0.05,there were no significant differences between the predicted values and the measured values. The established quantitative analysis models can be used to predict the contents of saponins in Pien Tze Huang accurately and the proposed method is simple,fast,non-destructive and environmentally friendly for the rapid detection and quality control of saponins in Pien Tze Huang.


Subject(s)
Chromatography, High Pressure Liquid , Drugs, Chinese Herbal , Chemistry , Least-Squares Analysis , Phytochemicals , Saponins , Spectroscopy, Near-Infrared
14.
Article in English | WPRIM | ID: wpr-773978

ABSTRACT

OBJECTIVE@#To investigate the effects of Pinggan Prescription (, PGP) on hypertension by the associated methods of metabonomic and pharmacodynamic.@*METHODS@#A total of 32 male spontaneously hypertensive rats (SHRs) were randomly divided into two groups by using the random number table method: a treatment group (n=18) and a model group (n=14). The Wistar rats (n=14) were used as the normal group. Different prescription were used to intervene three groups: the treatment group in which PGP extract was administered orally at a dose of 18.336 g/kg (PGP/body weight), and the model group in which physiological saline was administered at the equivalent dose. The same treatment was applied to the normal group as the model group. The blood pressure was measured by tail-cuff method, and pharmacodynamic indexes including cyclic adenosine monophosphate (cAMP) and angiotensin II (Ang II) were tested by enzyme-linked immunosorbent assay. The plasma samples from three groups were detected by gas chromatography-mass spectrometry (GC-MS).@*RESULTS@#Compared with the model group, blood pressure of treatment group was obviously reduced after continuous curing with PGP (P<0.01). The pharmacodynamic results illustrated that the content of Ang II increased with the raised blood pressure and the cAMP expressed the converse trend. After curing with PGP, the content of Ang II decreased, the difference between model group and treatment group was significant (P<0.01), and the cAMP expressed the converse trend. Five potential biomarkers were identified, including arachidonic acid, hexadecanoic acid, elaidic acid, octadecanedioic acid and 9,12-octadecadienoic acid. These metabolites had shown significantly changes as followed: arachidonic acid, hexadecanoic acid and elaidic acid were significantly higher and octadecanedioic acid and 9,12-octadecadienoic acid were lowered in the model group than those in the normal group. After the treatment of PGP, the metabolites had the trends of returning to normal along with the reduced blood pressure.@*CONCLUSIONS@#PGP intervention for hypertension played a major role in the metabolism of arachidonic acid and linoleic acid. Metabonomic with pharmacodynamic methods could be potentially powerful tools to investigate the mechanism of Chinese medicine.


Subject(s)
Animals , Biomarkers , Blood , Discriminant Analysis , Drugs, Chinese Herbal , Pharmacology , Gas Chromatography-Mass Spectrometry , Hypertension , Blood , Drug Therapy , Least-Squares Analysis , Male , Metabolic Networks and Pathways , Metabolomics , Models, Biological , Principal Component Analysis , Rats, Inbred SHR , Rats, Wistar
15.
Chinese Journal of Biotechnology ; (12): 1491-1499, 2019.
Article in Chinese | WPRIM | ID: wpr-771780

ABSTRACT

The quantity of biomass, glucose concentration and ethanol concentration are important parameters in ethanol fermentation. Traditional methods are usually based on samples for off-line measurement, which not only requires multiple instruments for test and analysis but also consumes notable time and effort, and therefore is inconvenient for real-time process control and optimization. In this study, an in-situ detection method based on the near-infrared (NIR) spectroscopy is proposed for measuring the above process parameters in real time. The in-situ measurement is carried out by using an immersion type NIR spectroscopy. A multi-output prediction model for simultaneously estimating the quantity of glucose, biomass and ethanol is established based on a multi-output least-squares support vector regression algorithm. The experimental results show that the proposed method can precisely measure the quantity of glucose, biomass and ethanol during the ethanol fermentation process. Compared to the existing partial-least-squares method for modeling and prediction of individual components, the proposed method could evidently improve the measurement accuracy and reliability.


Subject(s)
Ethanol , Fermentation , Least-Squares Analysis , Reproducibility of Results , Spectroscopy, Near-Infrared
16.
Article in English | WPRIM | ID: wpr-760638

ABSTRACT

BACKGROUND/OBJECTIVES: Lower circulating 25-hydroxyvitamin D [25(OH)D] levels are associated with a higher risk of hypertension (HTN); however, it remains unclear whether the relationship is causal. We aimed to evaluate the causal effects of circulating 25(OH)D levels on the prevalence of HTN in the Korean population using the Mendelian randomization (MR) approach. SUBJECTS/METHODS: Epidemiological data, serum 25(OH)D data, and genomic DNA biospecimens were obtained from 2,591 participants, a subset of the study population in the Korea National Health and Nutrition Survey 2011-2012. Five 25(OH)D-related single nucleotide polymorphisms (SNPs; DHCR7 rs12785878, CYP2R1 rs10741657, CYP2R1 rs12794714, CYP24A1 rs6013897, and GC rs2282679), identified a priori from genome-wide association studies, were used as instrument variables (IVs) for serum 25(OH)D levels. In the MR analysis, we performed IV analyses using the two-stage least squares method. RESULTS: In the observational analysis, circulating 25(OH)D levels were found to be inversely associated with the HTN prevalence in ordinary least squares models (odds ratio: 0.97, 95% confidence interval: 0.96, 0.99) after adjusting for the potential confounders. There were differences in the circulating 25(OH)D levels across genotypes of individual SNPs. In the MR analysis, using individual SNPs as IVs, 25(OH)D levels were not associated with the HTN prevalence. CONCLUSIONS: We found no association between genetically determined circulating 25(OH)D levels and HTN in Korean adults. Our results are listed owing to the relatively small sample size and possible weak instrument bias; therefore, further studies are needed to confirm these results.


Subject(s)
Adult , Bias , Blood Pressure , DNA , Genome-Wide Association Study , Genotype , Humans , Hypertension , Korea , Least-Squares Analysis , Methods , Nutrition Surveys , Polymorphism, Single Nucleotide , Prevalence , Random Allocation , Sample Size , Vitamin D , Vitamin D3 24-Hydroxylase
17.
Article in English | WPRIM | ID: wpr-719269

ABSTRACT

OBJECTIVES: The association between the spread of infectious diseases and climate parameters has been widely studied in recent decades. In this paper, we formulate, exploit, and compare three variations of the susceptible-infected-recovered (SIR) model incorporating climate data. The SIR model is a well-studied model to investigate the dynamics of influenza viruses; however, the improved versions of the classic model have been developed by introducing external factors into the model. METHODS: The modification models are derived by multiplying a linear combination of three complementary factors, namely, temperature (T), precipitation (P), and humidity (H) by the transmission rate. The performance of these proposed models is evaluated against the standard model for two outbreak seasons. RESULTS: The values of the root-mean-square error (RMSE) and the Akaike information criterion (AIC) improved as they declined from 8.76 to 7.05 and from 98.12 to 93.01 for season 2013/14, respectively. Similarly, for season 2014/15, the RMSE and AIC decreased from 8.10 to 6.45 and from 117.73 to 107.91, respectively. The estimated values of R(t) in the framework of the standard and modified SIR models are also compared. CONCLUSIONS: Through simulations, we determined that among the studied environmental factors, precipitation showed the strongest correlation with the transmission dynamics of influenza. Moreover, the SIR+P+T model is the most efficient for simulating the behavioral dynamics of influenza in the area of interest.


Subject(s)
Basic Reproduction Number , Climate , Communicable Diseases , Epidemiology , Humidity , Influenza, Human , Iran , Least-Squares Analysis , Orthomyxoviridae , Seasons
18.
Article in English | WPRIM | ID: wpr-764428

ABSTRACT

PURPOSE: The aim of this study was to evaluate the influence of polishing methods on the color stability of composite resins. MATERIALS AND METHODS: Two bulk-fill and four conventional resin composites were filled in cylindrical molds (6 mm diameter, 4 mm height) and light-cured. The specimens were stored in 34℃ distilled water for 24 h. Spectrophotometer was used to determine the color value according to the CIE L(*)a(*)b(*) color space. Each group was divided into three groups according to polishing methods (n = 5). Group 1 was control group (Mylar strip group), group 2 was polished with PoGo, and group 3 was polished with Sof-Lex Spiral wheels. Color evaluation was performed weekly for 4 weeks after immersion in 34℃ distilled water. The results were analyzed by generalized least squares method (P < 0.05). RESULTS: Generalized least squares analysis revealed that Sof-Lex Spiral wheels group showed the significantly lower ΔE values compared to PoGo and control group (P < 0.05). The ΔE values of polished group showed the significantly lower than the ΔE values of unpolished group (P < 0.05). Regarding color changes of composite resins, there was no significant difference between the ΔE values of Filtek Z250 and Filtek Z350 XT Universal restorative in all time intervals (P < 0.05). Tetric N-Ceram Bulk Fill showed the significantly lower ΔE values compared to other composite resins in 1, 2, 3 weeks (P < 0.05). CONCLUSION: Within the limitations of this study, polishing methods influence the color stabilities of composite resins. The group polished with Sof-Lex Spiral Wheels showed more resistance to discoloration than group polished with PoGo.


Subject(s)
Absorption , Composite Resins , Fungi , Immersion , Least-Squares Analysis , Methods , Water
20.
Epidemiology and Health ; : 2018021-2018.
Article in English | WPRIM | ID: wpr-786852

ABSTRACT

OBJECTIVES: We analyzed dietary patterns using reduced rank regression (RRR), and assessed how well the scores extracted by RRR predicted stroke in comparison to the scores produced by partial least squares and principal component regression models.METHODS: Dietary data at baseline were used to extract dietary patterns using the 3 methods, along with 4 response variables: body mass index, fibrinogen, interleukin-6, and low-density lipoprotein cholesterol. The analyses were based on 5,468 males and females aged 45–84 years who had no clinical cardiovascular disease, using data from the Multi-Ethnic Study of Atherosclerosis.RESULTS: The primary factor derived by RRR was positively associated with stroke incidence in both models. The first model was adjusted for sex and race and the second model was adjusted for the variables in model 1 as well as smoking, physical activity, family and sibling history of stroke, the use of any lipid-lowering medication, the use of any anti-hypertensive medication, hypertension, and history of myocardial infarction (model 1: hazard ratio [HR], 7.49; 95% confidence interval [CI], 1.66 to 33.69; p for trend=0.01; model 2: HR, 6.83; 95% CI, 1.51 to 30.87 for quintile 5 compared with the reference category; p for trend=0.02).CONCLUSIONS: Based primarily on RRR, we identified that a dietary pattern high in fats and oils, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, and fried potatoes and low in dark-yellow and cruciferous vegetables may increase the incidence of ischemic stroke.


Subject(s)
Atherosclerosis , Body Mass Index , Cardiovascular Diseases , Chickens , Cholesterol , Continental Population Groups , Diet , Fabaceae , Fats , Female , Fibrinogen , Humans , Hypertension , Incidence , Interleukin-6 , Least-Squares Analysis , Lipoproteins , Lycopersicon esculentum , Male , Meat , Methods , Motor Activity , Myocardial Infarction , Oils , Ovum , Poultry , Risk Factors , Siblings , Smoke , Smoking , Solanum tuberosum , Stroke , Tuna , Vegetables
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